Exploring the application and decision optimization of climate-smart agriculture within land-energy-food-waste nexus

IF 10.9 1区 环境科学与生态学 Q1 ENVIRONMENTAL STUDIES Sustainable Production and Consumption Pub Date : 2024-09-06 DOI:10.1016/j.spc.2024.08.019
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Abstract

The escalating threat of climate change from greenhouse gas (GHG) emissions increasingly threatens the stability of agricultural systems, emphasizing the pressing necessity to transition towards sustainable, low-carbon practices. Climate-smart agriculture (CSA) is an evolving approach to balance heightened crop productivity, reduced GHG emissions, and enhanced resource adaptability to climate change. A comprehensive model was developed to facilitate the sustainable and coordinated development of land, energy, food, and waste nexus systems. This study seeks to tackle the pressing necessity by incorporating advanced modeling techniques to enhance resource allocation and decision-making in agricultural systems, aiming for a triple win in reducing GHG emissions, enhancing food security, and promoting economic sustainability. An integrated approach harnessing life cycle assessment, system dynamics model, and multi-objective optimization methodologies was employed to evaluate the effects, trade-offs, and synergies of resource allocation in the context of CSA practices. In Jiangxi Province, China, a case study demonstrated notable reductions in overall carbon footprints, ranging from 6.02 % to 12.03 %. Additionally, applying the Non-dominated Sorting Genetic Algorithm II optimization algorithm to the model led to significant enhancements, such as an 11.24 % increase in grain nutrient availability, a 20.99 % boost in economic returns, and a 19.36 % decrease in GHG emissions. The findings underscore the efficacy of optimizing resource allocation to attain economic, environmental, and social advantages and curb carbon emissions. Moreover, pivotal policy recommendations encompass land use transformation, optimal food production allocation, and bioenergy production restructuring. Enforcing the practices of CSA and integrating them with carbon market transactions are crucial for sustainable agricultural development. This innovative framework provides a sustainable global agricultural management model with a low-carbon footprint, which is particularly beneficial in resource-scarce regions with competing policy objectives.

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探索气候智能型农业在土地-能源-粮食-废物关系中的应用和决策优化
温室气体(GHG)排放造成的气候变化威胁不断升级,日益威胁着农业系统的稳定,这凸显了向可持续、低碳做法过渡的迫切需要。气候智能型农业(CSA)是一种不断发展的方法,可在提高作物生产率、减少温室气体排放和增强资源对气候变化的适应性之间取得平衡。为促进土地、能源、粮食和废物关系系统的可持续协调发展,开发了一个综合模型。这项研究旨在通过采用先进的建模技术来加强农业系统的资源分配和决策,从而实现减少温室气体排放、加强粮食安全和促进经济可持续发展的三赢目标。研究采用了生命周期评估、系统动力学模型和多目标优化方法等综合方法,以评估 CSA 实践中资源配置的效果、权衡和协同作用。在中国江西省进行的一项案例研究表明,总体碳足迹显著减少,幅度从 6.02% 到 12.03%。此外,在模型中应用非优势排序遗传算法 II 优化算法后,效果显著增强,例如谷物养分可用性提高了 11.24%,经济收益提高了 20.99%,温室气体排放量减少了 19.36%。研究结果凸显了优化资源配置以实现经济、环境和社会优势以及遏制碳排放的功效。此外,关键的政策建议包括土地利用转型、优化粮食生产分配和生物能源生产结构调整。实施 CSA 实践并将其与碳市场交易相结合,对于可持续农业发展至关重要。这一创新框架提供了一种低碳足迹的可持续全球农业管理模式,对于资源稀缺、政策目标相互竞争的地区尤为有益。
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来源期刊
Sustainable Production and Consumption
Sustainable Production and Consumption Environmental Science-Environmental Engineering
CiteScore
17.40
自引率
7.40%
发文量
389
审稿时长
13 days
期刊介绍: Sustainable production and consumption refers to the production and utilization of goods and services in a way that benefits society, is economically viable, and has minimal environmental impact throughout its entire lifespan. Our journal is dedicated to publishing top-notch interdisciplinary research and practical studies in this emerging field. We take a distinctive approach by examining the interplay between technology, consumption patterns, and policy to identify sustainable solutions for both production and consumption systems.
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